Complexity of geometric inductive reasoning tasks

An item response theory analysis of the matrix reasoning item bank (MaRs-IB)

Matrix reasoning tasks are among the most widely used measures of cognitive ability in the behavioral sciences, but the lack of matrix reasoning tests in the public domain complicates their use. Here, we present an extensive investigation and psychometric validation of the matrix reasoning item bank (MaRs-IB), an open-access set of matrix reasoning items. In a first study, we calibrate the psychometric functioning of the items in the MaRs-IB in a large sample of adult participants (N = 1501). Using additive multilevel item structure models, we establish that the MaRs-IB has many desirable psychometric properties: its items span a wide range of difficulty, possess medium-to-large levels of discrimination, and exhibit robust associations between item complexity and difficulty. However, we also find that item clones are not always psychometrically equivalent and cannot be assumed to be exchangeable. In a second study, we demonstrate how experimenters can use the estimated item parameters to design new matrix reasoning tests using optimal item assembly. Specifically, we design and validate two new sets of test forms in an independent sample of adults (N = 600). We find these new tests possess good reliability and convergent validity with an established measure of matrix reasoning. We hope that the materials and results made available here will encourage experimenters to use the MaRs-IB in their research.

The Development of Relational Reasoning: An Eyetracking Analysis of Strategy Use and Adaptation in Children and Adults Performing Matrix Completion

Relational reasoning is a key component of fluid intelligence and an important predictor of academic achievement. Relational reasoning is commonly assessed using matrix completion tasks, in which participants see an incomplete matrix of items that vary on different dimensions and select a response that best completes the matrix based on the relations among items. Performance on such assessments increases dramatically across childhood into adulthood. However, despite widespread use, little is known about the strategies associated with good or poor matrix completion performance in childhood. This study examined the strategies children and adults use to solve matrix completion problems, how those strategies change with age, and whether children and adults adapt strategies to difficulty. We used eyetracking to infer matrix completion strategy use in 6- and 9-year-old children and adults. Across ages, scanning across matrix rows and columns predicted good overall performance, and quicker and higher rates of consulting potential answers predicted poor performance, indicating that optimal matrix completion strategies are similar across development. Indices of good strategy use increased across childhood. As problems increased in difficulty, children and adults increased their scanning of matrix rows and columns, and adults and 9-year-olds also shifted strategies to rely more on consulting potential answers. Adapting strategies to matrix difficulty, particularly increased scanning of rows and columns, was associated with good overall performance in both children and adults. These findings underscore the importance of both spontaneous and adaptive strategy use in individual differences in relational reasoning and its development.

Knowledge Representations: Individual Differences in Novel Problem Solving

The present study investigates how the quality of knowledge representations contributes to rule transfer in a problem-solving context and how working memory capacity (WMC) might contribute to the subsequent failure or success in transferring the relevant information. Participants were trained on individual figural analogy rules and then asked to rate the subjective similarity of the rules to determine how abstract their rule representations were. This rule representation score, along with other measures (WMC and fluid intelligence measures), was used to predict accuracy on a set of novel figural analogy test items, of which half included only the trained rules, and half were comprised of entirely new rules. The results indicated that the training improved performance on the test items and that WMC largely explained the ability to transfer rules. Although the rule representation scores did not predict accuracy on the trained items, rule representation scores did uniquely explain performance on the figural analogies task, even after accounting for WMC and fluid intelligence. These results indicate that WMC plays a large role in knowledge transfer, even when transferring to a more complex problem-solving context, and that rule representations may be important for novel problem solving.

A Log File Analysis on the Validity of Partial Solutions in Figural Matrices Tests

As a component of many intelligence test batteries, figural matrices tests are an effective way to assess reasoning, which is considered a core ability of intelligence. Traditionally, the sum of correct items is used as a performance indicator (total solution procedure). However, recent advances in the development of computer-based figural matrices tests allow additional indicators to be considered for scoring. In two studies, we focused on the added value of a partial solution procedure employing log file analyses from a computer-based figural matrices test. In the first study (n = 198), we explored the internal validity of this procedure by applying both an exploratory bottom-up approach (using sequence analyses) and a complementary top-down approach (using rule jumps, an indicator taken from relevant studies). Both approaches confirmed that higher scores in the partial solution procedure were associated with higher structuredness in participants' response behavior. In the second study (n = 169), we examined the external validity by correlating the partial solution procedure in addition to the total solution procedure with a Grade Point Average (GPA) criterion. The partial solution procedure showed an advantage over the total solution procedure in predicting GPA, especially at lower ability levels. The implications of the results and their applicability to other tests are discussed.

Graph Mapping: A novel and simple test to validly assess fluid reasoning

We present Graph Mapping - a simple and effective computerized test of fluid intelligence (reasoning ability). The test requires structure mapping - a key component of the reasoning process. Participants are asked to map a pair of corresponding nodes across two mathematically isomorphic but visually different graphs. The test difficulty can be easily manipulated - the more complex structurally and dissimilar visually the graphs, the higher response error rate. Graph Mapping offers high flexibility in item generation, ranging from trivial to extremally difficult items, supporting progressive item sequences suitable for correlational studies. It also allows multiple item instances (clones) at a fixed difficulty level as well as full item randomization, both particularly suitable for within-subject experimental designs, longitudinal studies, and adaptive testing. The test has short administration times and is unfamiliar to participants, yielding practical advantages. Graph Mapping has excellent psychometric properties: Its convergent validity and reliability is comparable to the three leading traditional fluid reasoning tests. The convenient software allows a researcher to design the optimal test variant for a given study and sample. Graph Mapping can be downloaded from: https://osf.io/wh7zv/.

Cognitive segmentation and fluid reasoning in childhood

The ability to solve novel complex problems predicts success in a wide range of areas. Recent research suggests that the ability to cognitively segment complex problems into smaller parts constrains nonverbal reasoning in adults. This study aimed to test whether cognitively segmenting problems improves nonverbal reasoning performance for children as it does for adults. A total of 115 children aged 6-10 years completed two versions of a modified traditional matrix reasoning task in which demands on working memory, integration, and processing speed were minimised, such that the only significant requirement was to break each problem into its constituent parts. In one version of the task, participants were presented with a traditional 2×2 Matrix and asked to draw the missing matrix item into a response box below. In a second version, the problem was broken down into its component features across three separate cells, reducing the need for participants to segment the problem. As with adults, performance was better in the condition in which the problems were separated into component parts. Children with lower fluid intelligence did not benefit more in the separated condition than children with higher fluid intelligence, and there was no evidence that segmenting problems was more beneficial for younger than older children. This study demonstrates that cognitive segmentation is a critical component of complex problem-solving for children, as it is for adults. By forcing children to focus their attention on separate parts of a complex visual problem, their performance can be dramatically improved.

Fluid Intelligence Emerges from Representing Relations

Based on recent findings in cognitive neuroscience and psychology as well as computational models of working memory and reasoning, I argue that fluid intelligence (fluid reasoning) can amount to representing in the mind the key relation(s) for the task at hand. Effective representation of relations allows for enormous flexibility of thinking but depends on the validity and robustness of the dynamic patterns of argument–object (role–filler) bindings, which encode relations in the brain. Such a reconceptualization of the fluid intelligence construct allows for the simplification and purification of its models, tests, and potential brain mechanisms.

Cross-cultural differences in visuo-spatial processing and the culture-fairness of visuo-spatial intelligence tests: an integrative review and a model for matrices tasks

Visuo-spatial reasoning tests, such as Raven's matrices, Cattell's culture-fair test, or various subtests of the Wechsler scales, are frequently used to estimate intelligence scores in the context of inter-racial comparisons. This has led to several high-profile works claiming that certain ethnic groups have lower intelligence than others, presumably due to genetic inferiority. This logic is predicated on the assumption that such visuo-spatial tests, because they are non-verbal, must be culture-fair: that their solution process does not significantly draw on factors that vary from one culture to the next. This assumption of culture-fairness is dubious at best and has been questioned by many authors. In this article, I review the substantial body of psychological and ethnographic literature which has demonstrated that the perception, manipulation and conceptualization of visuo-spatial information differs significantly across cultures, in a way that is relevant to intelligence tests. I then outline a model of how these inter-cultural differences can affect seven major steps of the solution process for Raven's matrices, with a brief discussion of other visuo-spatial reasoning tests. Overall, a number of cultural assumptions appear to be deeply ingrained in all visuo-spatial reasoning tests, to the extent that it disqualifies the view of such tests as intrinsically culture-fair and makes it impossible to draw clear-cut conclusions from average score differences between ethnic groups.

Neural correlates of individual variation in two-back working memory and the relationship with fluid intelligence

Working memory has been examined extensively using the N-back task. However, less is known about the neural bases underlying individual variation in the accuracy rate (AR) and reaction time (RT) as metrics of N-back performance. Whereas AR indexes the overall performance, RT may more specifically reflect the efficiency in updating target identify. Further, studies have associated fluid intelligence (Gf) with working memory, but the cerebral correlates shared between Gf and N-back performance remain unclear. We addressed these issues using the Human Connectome Project dataset. We quantified the differences in AR (critical success index or CSI) and RT between 2- and 0-backs (CSI_2–0 and RT_2–0) and identified the neural correlates of individual variation in CSI_2–0, RT_2–0, and Gf, as indexed by the number of correct items scored in the Raven’s Standard Progressive Matrices (RSPM) test. The results showed that CSI_2–0 and RT_2–0 were negatively correlated, suggesting that a prolonged response time did not facilitate accuracy. At voxel p < 0.05, FWE-corrected, the pre-supplementary motor area (preSMA), bilateral frontoparietal cortex (biFPC) and right anterior insula (rAI) showed activities in negative correlation with CSI_2–0 and positive correlation with RT_2–0. In contrast, a cluster in the dorsal anterior cingulate cortex (dACC) bordering the SMA showed activities in positive correlation with CSI_2–0 and negative correlation with RT_2–0. Further, path analyses showed a significant fit of the model dACC → RT_2–0 → CSI_2–0, suggesting a critical role of target switching in determining performance accuracy. Individual variations in RT_2–0 and Gf were positively correlated, although the effect size was small (f² = 0.0246). RT_2–0 and Gf shared activities both in positive correlation with the preSMA, biFPC, rAI, and dorsal precuneus. These results together suggest inter-related neural substrates of individual variation in N-back performance and highlight a complex relationship in the neural processes supporting 2-back and RSPM performance.

Involvement of the Right Dorsolateral Prefrontal Cortex in Numerical Rule Induction: A Transcranial Direct Current Stimulation Study

Numerical inductive reasoning has been considered as one of the most important higher cognitive functions of the human brain. Importantly, previous behavioral studies have consistently reported that one critical component of numerical inductive reasoning is checking, which often occurs when a discrepant element is discovered, and reprocessing is needed to determine whether the discrepancy is an error of the original series. However, less is known about the neural mechanism underlying the checking process. Given that the checking effect involves cognitive control processes, such as the incongruent resolution, that are linked to the right dorsolateral prefrontal cortex (DLPFC), this study hypothesizes that the right DLPFC may play a specific role in the checking process. To test the hypothesis, this study utilized the transcranial direct current stimulation (tDCS), a non-invasive brain stimulation method that could modulate cortical excitability, and examined whether and how the stimulation of the right DLPFC via tDCS could modulate the checking effect during a number-series completion problem task. Ninety healthy participants were allocated to one of the anodal, cathodal, and sham groups. Subjects were required to verify whether number sequences formed rule-based series, and checking effect was assessed by the difference in performance between invalid and valid conditions. It was found that significantly longer response times (RTs) were exhibited in invalid condition compared with valid condition in groups of anodal, cathodal, and sham tDCS. Furthermore, the anodal tDCS significantly shortened the checking effect than those of the cathodal and sham groups, whereas no significantly prolonged checking effect was detected in the cathodal group. The current findings indicated that anodal tDCS affected the process of checking, which suggested that the right DLPFC might play a critical role in the checking process of numerical inductive reasoning by inhibiting incongruent response.

AI, visual imagery, and a case study on the challenges posed by human intelligence tests

Observations abound about the power of visual imagery in human intelligence, from how Nobel prize-winning physicists make their discoveries to how children understand bedtime stories. These observations raise an important question for cognitive science, which is, what are the computations taking place in someone's mind when they use visual imagery? Answering this question is not easy and will require much continued research across the multiple disciplines of cognitive science. Here, we focus on a related and more circumscribed question from the perspective of artificial intelligence (AI): If you have an intelligent agent that uses visual imagery-based knowledge representations and reasoning operations, then what kinds of problem solving might be possible, and how would such problem solving work? We highlight recent progress in AI toward answering these questions in the domain of visuospatial reasoning, looking at a case study of how imagery-based artificial agents can solve visuospatial intelligence tests. In particular, we first examine several variations of imagery-based knowledge representations and problem-solving strategies that are sufficient for solving problems from the Raven's Progressive Matrices intelligence test. We then look at how artificial agents, instead of being designed manually by AI researchers, might learn portions of their own knowledge and reasoning procedures from experience, including learning visuospatial domain knowledge, learning and generalizing problem-solving strategies, and learning the actual definition of the task in the first place.

Socio-affective and cognitive predictors of social adaptation in vulnerable contexts

People living in vulnerable environments face a harder set of challenges adapting to their context. Nevertheless, an important number of them adapt successfully. However, which cognitive and socio-affective variables are specifically related to these variations in social adaptation in vulnerable contexts has not been fully understood nor directly addressed. Here we evaluated socio-affective variables (anxious attachment style, internal locus of control, self-esteem and stress) and cognitive variables (fluid intelligence, crystallized intelligence, working memory, numeracy, probabilistic reasoning and logical reasoning) to explain variations in social adaptation in a sample of 232 adults living in vulnerable contexts (M = 42.3, SD = 14.9, equal amount of men and women). Our results show that an important amount of variance in social adaptation can be explained by socio-affective variables, principally by self-esteem, while cognitive variables also contributed significantly. As far as we know, this is one of the first steps towards understanding the role of cognitive and socio-affective features on social adaptation. In the long run, this area of research could play an important role on the assignation of resources to ease people's integration into society. Our data and R analysis scripts can be found at: https://osf.io/egxy5/.

Testing a Cognitive Control Model of Human Intelligence

The definition of human intelligence and its underlying psychological constructs have long been debated. Although previous studies have investigated the fundamental cognitive functions determining intellectual abilities, such as the broadly defined executive functions including working memory, the core process has yet to be identified. A potential candidate for such a role might be cognitive control, a psychological construct for the coordination of thoughts and actions under conditions of uncertainty. In this study, we tested a cognitive control model of intellectual ability by examining the association between cognitive control, measured by a perceptual decision-making task and by the attention network test, and general intelligence including components of fluid intelligence (Gf, concerning the ability to solve problems by abstraction) and crystalized intelligence (Gc, related to learning from prior knowledge and experience) measured by the Wechsler Adult Intelligence Scale. We also examined the potential role of cognitive control as a core process involved in another determinant of intellectual abilities, the working memory, measured by the N-back tasks and the working memory complex span tasks. The relationship among intelligence, cognitive control, and working memory was examined using structural equation modeling. Results showed that cognitive control shared a large amount of variance with working memory and both measures were strongly associated with Gf and Gc, with a stronger association with Gf than Gc. These findings suggest that cognitive control, serving as a core construct of executive functions, contributes substantially to general intellectual ability, especially fluid intelligence.

The Role of Visuospatial Ability in the Raven’s Progressive Matrices

Abstract. Debate surrounding the role of visuospatial ability in performance on the Raven’s Progressive Matrices (RPM) has existed since their conception. This issue has yet to be adequately resolved, and may have implications regarding sex differences in scores. Therefore, this study aimed to examine the relationship between RPM performance, visuospatial ability and fluid ability, and any sex differences in these relationships. Data were obtained from three samples: two University samples completed the Advanced RPM and one population-based sample of men completed the Standard RPM. All samples additionally completed an alternative measure of fluid ability, and one or more measures of visuospatial ability. Structural equation modeling was used to examine the relationships between performance on the visuospatial and fluid ability tests and performance on the RPM. Visuospatial ability was found to significantly contribute to performance on the RPM, over and above fluid ability, supporting the contention that visuospatial ability is involved in RPM performance. No sex differences were found in this relationship, although sex differences in visuospatial ability may explain sex differences in RPM scores.

Is the Correlation between Storage Capacity and Matrix Reasoning Driven by the Storage of Partial Solutions? A Pilot Study of an Experimental Approach

Working memory capacity (WMC) and reasoning abilities-as assessed by figural matrices tests-are substantially correlated. It is controversially discussed whether this correlation is only caused by controlled attention or also by storage capacity. This study aims at investigating storage of partial solutions as a possible mechanism by which storage capacity may contribute to solving figural matrices tests. For this purpose, we analyzed how an experimental manipulation of storage demands changes the pattern of correlations between WMC and performance in a matrix task. We manipulated the storage demands by applying two test formats: one providing the externalization of partial solutions and one without the possibility of externalization. Storage capacity was assessed by different types of change detection tasks. We found substantial correlations between storage capacity and matrices test performance, but they were of comparable size for both test formats. We take this as evidence that the necessity to store partial solutions is not the limiting factor which causes the association between storage capacity and matrices test. It is discussed how this approach can be used to investigate alternative mechanisms by that storage may influence performance in matrices tests.

Using Cognitive Screening Tests in Audiology

PURPOSE

The population of the United States is aging. Those older adults are living longer than ever and have an increased desire for social participation. As a result, audiologists are likely to see an increased demand for service by older clients whose communication difficulty is caused by a combination of hearing loss and cognitive impairment. For these individuals, early detection of mild cognitive impairment is critical for providing timely medical intervention and social support.

METHOD

This tutorial provides information about cognition of older adults, mild cognitive impairment, and cognitive screening tests, with the purpose of assisting audiologists in identifying and appropriately referring potential cases of cognitive impairment.

RESULTS

Topics addressed also include how to administer cognitive screening tests on individuals with hearing loss, how to use test results in audiology practice, and the potential of using cognitive screening tests for evaluating the benefit of clinical interventions.

CONCLUSIONS

As health care professionals who serve the aging population, audiologists are likely to encounter cases of undiagnosed cognitive impairment. In order to provide timely referral for medical assistance as well as an optimized individual outcome of audiologic interventions, audiologists should be trained to recognize an abnormality in older clients' cognitive status.

Progression paths in children's problem solving: The influence of dynamic testing, initial variability, and working memory

The current study investigated developmental trajectories of analogical reasoning performance of 104 7- and 8-year-old children. We employed a microgenetic research method and multilevel analysis to examine the influence of several background variables and experimental treatment on the children's developmental trajectories. Our participants were divided into two treatment groups: repeated practice alone and repeated practice with training. Each child received an initial working memory assessment and was subsequently asked to solve figural analogies on each of several sessions. We examined children's analogical problem-solving behavior and their subsequent verbal accounts of their employed solving processes. We also investigated the influence of verbal and visual-spatial working memory capacity and initial variability in strategy use on analogical reasoning development. Results indicated that children in both treatment groups improved but that gains were greater for those who had received training. Training also reduced the influence of children's initial variability in the use of analogical strategies with the degree of improvement in reasoning largely unrelated to working memory capacity. Findings from this study demonstrate the value of a microgenetic research method and the use of multilevel analysis to examine inter- and intra-individual change in problem-solving processes.

Excelência profissional: a convergência necessária de variáveis psicológicas

O estudo da excelência humana assume essencialmente dois enfoques, um deles acentuando as variáveis psicológicas dos indivíduos e outro enfatizando as aquisições decorrentes da prática ou treino deliberado. Neste artigo procurou-se integrar tais estudos, propondo que o surgimento e a manutenção da excelência pressupõem uma constelação de variáveis psicológicas que vão para além da alta capacidade intelectual. Mais concretamente, descreveu-se um conjunto de variáveis cognitivas, motivacionais e de personalidade, assumidas como relevantes na excelência profissional em diferentes áreas de desempenho e de conhecimento. No seio das variáveis cognitivas e, fazendo uma ponte com as variáveis de personalidade, destaca-se o papel da criatividade para a excelência, reconhecendo a sua particular relevância em algumas áreas de realização profissional.

The quadratic relationship between difficulty of intelligence test items and their correlations with working memory

Fluid intelligence (Gf) is a crucial cognitive ability that involves abstract reasoning in order to solve novel problems. Recent research demonstrated that Gf strongly depends on the individual effectiveness of working memory (WM). We investigated a popular claim that if the storage capacity underlay the WM–Gf correlation, then such a correlation should increase with an increasing number of items or rules (load) in a Gf-test. As often no such link is observed, on that basis the storage-capacity account is rejected, and alternative accounts of Gf (e.g., related to executive control or processing speed) are proposed. Using both analytical inference and numerical simulations, we demonstrated that the load-dependent change in correlation is primarily a function of the amount of floor/ceiling effect for particular items. Thus, the item-wise WM correlation of a Gf-test depends on its overall difficulty, and the difficulty distribution across its items. When the early test items yield huge ceiling, but the late items do not approach floor, that correlation will increase throughout the test. If the early items locate themselves between ceiling and floor, but the late items approach floor, the respective correlation will decrease. For a hallmark Gf-test, the Raven-test, whose items span from ceiling to floor, the quadratic relationship is expected, and it was shown empirically using a large sample and two types of WMC tasks. In consequence, no changes in correlation due to varying WM/Gf load, or lack of them, can yield an argument for or against any theory of WM/Gf. Moreover, as the mathematical properties of the correlation formula make it relatively immune to ceiling/floor effects for overall moderate correlations, only minor changes (if any) in the WM–Gf correlation should be expected for many psychological tests.

Die Matrizenkonstruktionsaufgabe

Figurale Matrizenaufgaben stellen eine bedeutsames Aufgabenformat im Bereich der Diagnostik kognitiver Fähigkeiten dar. Während die Konstruktion der Aufgabenstämme in der Literatur relativ gut dokumentiert ist, finden sich nur wenige Hinweise zur Konstruktion der für die Vorgabe benötigten Distraktoren. Dies erweist sich als problematisch, da ein Einfluss der Distraktorgestaltung auf das Bearbeitungsverhalten von Testpersonen vermutet werden kann. Die Matrizenkonstruktionsaufgabe stellt ein alternatives Format zur Vorgabe figuraler Matrizen dar. In diesem müssen die Testpersonen die Lösung der Aufgaben in einer computerisierten Testumgebung selbst konstruieren, weshalb auf die Verwendung von Distraktoren verzichtet werden kann. Im Rahmen der Studie wurden einer Stichprobe von 318 Studierenden 40 Matrizenkonstruktionsaufgaben vorgegeben. Die Ergebnisse deuten auf eine gute psychometrische Eignung des Aufgabenformats hin: Es konnte eine große Bandbreite an Aufgabenschwierigkeiten realisiert werden. Die Aufgaben erfassen eine latente Fähigkeitsdimension und weisen eine gute Konstrukt- und Kriteriumsvalidität auf. In der Diskussion werden Perspektiven zur Weiterentwicklung des Aufgabenformats besprochen.

Does IQ measure ability for complex cognition?

A popular conception of the “intelligence,” or g, thought to be measured by IQ tests, is that of a cognitive “strength” variable that facilitates complex cognition such as reasoning and problem solving. Yet test items seem remarkably un-complex when compared with everyday cognition. Here, typical verbal and non-verbal test items are examined and arguments asserting their complexity are challenged. In contrast, several lines of research indicate how “real life” cognition is much more complex than that required by such items. The claim that an IQ-job performance correlation is stronger for more complex jobs is also challenged. This leads to the suggestion that other sources of variance, including cultural, affective, and other non-cognitive factors, may explain differences in test performance. An alternative explanation for the still-puzzling “Flynn effect” is proposed, with the idea that IQ differences reflect cultural “distance” (from possibly equal, but different, complexities) rather than a universal cognitive “strength.”

Confirming the cognition of rising scores: Fox and Mitchum (2013) predicts violations of measurement invariance in series completion between age-matched cohorts

The trend of rising scores on intelligence tests raises important questions about the comparability of variation within and between time periods. Descriptions of the processes that mediate selection of item responses provide meaningful psychological criteria upon which to base such comparisons. In a recent paper, Fox and Mitchum presented and tested a cognitive theory of rising scores on analogical and inductive reasoning tests that is specific enough to make novel predictions about cohort differences in patterns of item responses for tests such as the Raven’s Matrices. In this paper we extend the same proposal in two important ways by (1) testing it against a dataset that enables the effects of cohort to be isolated from those of age, and (2) applying it to two other inductive reasoning tests that exhibit large Flynn effects: Letter Series and Word Series. Following specification and testing of a confirmatory item response model, predicted violations of measurement invariance are observed between two age-matched cohorts that are separated by only 20 years, as members of the later cohort are found to map objects at higher levels of abstraction than members of the earlier cohort who possess the same overall level of ability. Results have implications for the Flynn effect and cognitive aging while underscoring the value of establishing psychological criteria for equating members of distinct groups who achieve the same scores.

Task structure complexity and goal neglect in typically developing children

Goal neglect is a failure to enact task requirements despite being able to accurately report them. In this study, we introduce a new child-appropriate experimental paradigm to measure goal neglect in children between 7 and 11 years of age and test the hypothesis that the complexity of an action plan, not real-time trial demands, increases goal neglect. A total of 66 children (Mage=9.50 years) were administered a Feature Match task. Half of the children were given four rules for matching, and half were given three rules for matching. After practice, the four-rules group was told to ignore the additional rule, and both groups completed an identical three-rules task. The results showed that the extra rule increased goal neglect and its correlation with fluid intelligence. Although intermittent trial errors were correlated with fluid intelligence for both groups, only in the four-rules group were systematic rule failures (i.e., goal neglect) correlated with fluid intelligence. Task performance improved with chronological age; however, when controlling for the influence of fluid intelligence, the relationship between age and task performance was effectively removed. This suggests that a child's current level of fluid intelligence (and not age) determines task performance. We suggest that the relationship among goal neglect, complex task instructions, and fluid intelligence is linked to the mental preparation for future events, that is, mentally compiling verbal instructions into a set of activated goal representations in working memory that represent what is to be done and under what circumstances.

Employment of Item Response Theory to measure change in Children's Analogical Thinking Modifiability Test

Dynamic testing, with an intermediate phase of assistance, measures changes between pretest and post-test assuming a common metric between them. To test this assumption we applied the Item Response Theory in the responses of 69 children to dynamic cognitive testing Children's Analogical Thinking Modifiability Test adapted, with 12 items, totaling 828 responses, with the purpose of verifying if the original scale yields the same results as the equalized scale obtained by Item Response Theory in terms of "changes quantifying". We followed the steps: 1) anchorage of the pre and post-test items through a cognitive analysis, finding 3 common items; 2) estimation of the items' difficulty level parameter and comparison of those; 3) equalization of the items and estimation of "thetas"; 4) comparison of the scales. The Children's Analogical Thinking Modifiability Test metric was similar to that estimated by the TRI, but it is necessary to differentiate the pre and post-test items' difficulty, adjusting it to samples with high and low performance.

The linear transformation model with frailties for the analysis of item response times

The item response times (RTs) collected from computerized testing represent an underutilized source of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. In this paper, we propose a semi-parametric model for RTs, the linear transformation model with a latent speed covariate, which combines the flexibility of non-parametric modelling and the brevity as well as interpretability of parametric modelling. In this new model, the RTs, after some non-parametric monotone transformation, become a linear model with latent speed as covariate plus an error term. The distribution of the error term implicitly defines the relationship between the RT and examinees' latent speeds; whereas the non-parametric transformation is able to describe various shapes of RT distributions. The linear transformation model represents a rich family of models that includes the Cox proportional hazards model, the Box-Cox normal model, and many other models as special cases. This new model is embedded in a hierarchical framework so that both RTs and responses are modelled simultaneously. A two-stage estimation method is proposed. In the first stage, the Markov chain Monte Carlo method is employed to estimate the parametric part of the model. In the second stage, an estimating equation method with a recursive algorithm is adopted to estimate the non-parametric transformation. Applicability of the new model is demonstrated with a simulation study and a real data application. Finally, methods to evaluate the model fit are suggested.

Process-based account for the effects of perceptual attention and executive attention on fluid intelligence: an integrative approach

Perceptual attention and executive attention represent two higher-order types of attention and associate with distinctly different ways of information processing. It is hypothesized that these two types of attention implicate different cognitive processes, which are assumed to account for the differential effects of perceptual attention and executive attention on fluid intelligence. Specifically, an encoding process is assumed to be crucial in completing the tasks of perceptual attention while two executive processes, updating and shifting, are stimulated in completing the tasks of executive attention. The proposed hypothesis was tested by means of an integrative approach combining experimental manipulations and psychometric modeling. In a sample of 210 participants the encoding process has proven indispensable in completing the tasks of perceptual attention, and this process accounted for a considerable part of fluid intelligence that was assessed by two figural reasoning tests. In contrast, the two executive processes, updating and shifting, turned out to be necessary in performance according to the tasks of executive attention and these processes accounted for a larger part of the variance in fluid intelligence than that of the processes underlying perceptual attention.